A group detection tool (“GDT”) is a mathematical routine applied to data describing known associations among individuals to detect clusters of persons who are likely to be involved in pursuit of a common goal or interest, to share a communicable disease, or to otherwise be involved together in a way that suggests more than a casual relationship. A GDT may detect clusters of people, diseases, biomedical events, fraud and terrorist cells where there is a common goal, interest or other observable common threads or co-occurrence. The efficacy of such a tool may be gauged, at least in part, by measures of:                1) Delineation accuracy, showing how much difference there is between groups inferred by application of a GDT and their real-world counter-parts; and        2) Inference utility, describing the accuracy and reliability of inferences as to allegiances or interests of individuals derived from analysis of groups identified by a GDT.        
The magnitude of the problem of defining quantifiers for such measures to support evaluation of GDTs depends on the availability of information on the existence and composition of groups. Given information on the composition of real-world groups, quantifiers for measures of delineation accuracy and interpretability can be readily defined in terms of differences between the membership of known groups and the ones identified with the GDT. Absent any information on real-world groups, however, there is no basis for determining such differences. In this case efficacy of a GDT must be inferred from statistics that can be derived and interpreted without any knowledge of actual groups or assumptions as to their likely effects on known associations.